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SAHF: Unsupervised Texture-Based Multiscale with Multicolor Method for Retinal Vessel Delineation

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Advances in Visual Computing (ISVC 2016)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 10072))

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Abstract

Automatic vessel delineation has been challenging due to complexities during the acquisition of retinal images. Although, great progress have been made in this field, it remains the subject of on-going research as there is need to further improve on the delineation of more large and thinner retinal vessels as well as the computational speed. Texture and color are promising, as they are very good features applied for object detection in computer vision. This paper presents an investigatory study on sum average Haralick feature (SAHF) using multi-scale approach over two different color spaces, CIElab and RGB, for the delineation of retinal vessels. Experimental results show that the method presented in this paper is robust for the delineation of retinal vessels having achieved fast computational speed with the maximum average accuracy of 95.67% and maximum average sensitivity of 81.12% on DRIVE database. When compared with the previous methods, the method investigated in this paper achieves higher average accuracy and sensitivity rates on DRIVE.

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Acknowledgement

We thank DRIVE [1] for making the retinal images dataset publicly available.

Author information

Authors and Affiliations

  1. School of Engineering, University of KwaZulu-Natal, Durban, South Africa

    Temitope Mapayi & Jules-Raymond Tapamo

Authors
  1. Temitope Mapayi
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  2. Jules-Raymond Tapamo
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Corresponding author

Correspondence to Jules-Raymond Tapamo .

Editor information

Editors and Affiliations

  1. University of Nevada , Reno, Nevada, USA

    George Bebis

  2. NASA Ames Research Center , Moffett Field, California, USA

    Richard Boyle

  3. Lawrence Berkeley National Laboratory , Berkeley, California, USA

    Bahram Parvin

  4. Desert Research Institute , Reno, Nevada, USA

    Darko Koracin

  5. The Australian National University , O'Malley, Aust Capital Terr, Australia

    Fatih Porikli

  6. Pilot AI Labs , Redwood City, California, USA

    Sandra Skaff

  7. University of Florida , Gainesville, Florida, USA

    Alireza Entezari

  8. Google Inc. , Mountain View, California, USA

    Jianyuan Min

  9. Osaka University , Osaka, Japan

    Daisuke Iwai

  10. The MOVES Institute , Monterey, California, USA

    Amela Sadagic

  11. University of Arizona , Tucson, Arizona, USA

    Carlos Scheidegger

  12. Université Paris-Sud , Orsay, France

    Tobias Isenberg

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Mapayi, T., Tapamo, JR. (2016). SAHF: Unsupervised Texture-Based Multiscale with Multicolor Method for Retinal Vessel Delineation. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2016. Lecture Notes in Computer Science(), vol 10072. Springer, Cham. https://doi.org/10.1007/978-3-319-50835-1_57

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  • DOI: https://doi.org/10.1007/978-3-319-50835-1_57

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-50834-4

  • Online ISBN: 978-3-319-50835-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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